This invention relates to characterization of trajectories, and more particularly to use of text characterization for tasks including text-based querying and summarization.
Mobile sensor networks such as smart phones are playing an increasingly important role in our lives, and can be the source of very large and useful data about the users carrying them. Today it is not possible and/or is computationally prohibitive to take signals generated from sensors such as GPS streams and convert them into text-searchable systems. For an individual mobile node/user, such a system would automatically create a textual diary that captures the spatio-temporal activities of the mobile node/user. For example, the user could pose the query “What are the restaurants I visited during Sensys 2012?” or “What are the roads I drove on today?”. For groups of mobile nodes/users, such a system captures their spatio-temporal interactions, for example “Where did I meet with X during Sensys 2012?”, or “When did Y and X meet for the first time?”
Translating massive amounts of raw GPS data points into useful human-understandable information is not currently possible because (a) compared to fields such as machine learning and text mining, very little is known about handling these kinds of data sets, both in theory and practice, (b) the user interface of existing GPS applications, (e.g., Google Latitude) is more oriented to map-navigation than text search, and (c) the data involved can be huge (e.g., a single smart phone can generate on the order of 1 GByte of data per day).
The idea of collecting location data using the mobile phone is not new. For example, some systems have been used to collect users' GPS data from their mobile phones and determine their common transportation modes and environmental impact. Applications for tracking user activities and locations have also appeared in the commercial realm. Commercial applications are available that attempt to track user activities and locations. One such system allows users to check-in to locations that are confirmed to be nearby using GPS location data and produces a searchable timeline; however, data collection in this system is not automated. A system called Google Latitude that is available today can track where a user has been, once known locations are set up on the user's phone. A dashboard shows the user's activity on a high-level scale (i.e., work, home, out), as well as a list of previously visited locations. However, the current applications lack low-level activity recognition (e.g., “drinking coffee”) and searchable history. To the inventors' knowledge, no previous system provides text search capabilities over raw GPS-data.